Modeling human mobility responses to the large-scale spreading of infectious diseases.

Modeling human mobility responses to the large-scale spreading of infectious diseases.
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DOI:
10.1038/srep00062
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发表时间:
2011
期刊:
影响因子:
4.6
通讯作者:
Vespignani, Alessandro
Vespignani, Alessandro
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Meloni, Sandro;Perra, Nicola;Arenas, Alex;Gomez, Sergio;Moreno, Yamir;Vespignani, Alessandro

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目前对传染病的建模允许研究现实情景,包括人口异质性、社会结构和向下到个人层面的流动过程。流行病描述的现实主义的进步要求在建模框架内对个体对疾病存在的行为反应进行明确的建模。在这里,我们制定和分析了一个集合种群模型,该模型将几个自我发起的行为变化的场景整合到个体的流动模式中。我们发现,基于流行率的旅行限制不会改变流行病侵袭阈值。值得注意的是,我们在人工模拟和数据驱动的数值模拟中观察到,当旅行者决定避开高流行水平的地点时,这种自我发起的行为变化可能会促进疾病的传播。我们的结果指出,有关疾病的信息的实时可获得性以及人口中随之而来的行为变化可能会对疾病的遏制和缓解产生负面影响。
Current modeling of infectious diseases allows for the study of realistic scenarios that include population heterogeneity, social structures, and mobility processes down to the individual level. The advances in the realism of epidemic description call for the explicit modeling of individual behavioral responses to the presence of disease within modeling frameworks. Here we formulate and analyze a metapopulation model that incorporates several scenarios of self-initiated behavioral changes into the mobility patterns of individuals. We find that prevalence-based travel limitations do not alter the epidemic invasion threshold. Strikingly, we observe in both synthetic and data-driven numerical simulations that when travelers decide to avoid locations with high levels of prevalence, this self-initiated behavioral change may enhance disease spreading. Our results point out that the real-time availability of information on the disease and the ensuing behavioral changes in the population may produce a negative impact on disease containment and mitigation.
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